Seismic exploration involves surveying subterranean geological media for hydrocarbon deposits. A survey typically involves deploying seismic sources and seismic sensors at predetermined locations. The sources generate seismic waves, which propagate into the geological medium creating pressure changes and vibrations. Variations in physical properties of the geological medium give rise to changes in certain properties of the seismic waves, such as their direction of propagation and other properties.
Portions of the seismic waves reach the seismic sensors. Some seismic sensors are sensitive to pressure changes (e.g., hydrophones), others to particle motion (e.g., geophones), and industrial surveys may deploy one type of sensor or both. In response to the detected seismic waves, the sensors generate corresponding electrical signals, known as traces, and record them in storage media as seismic data. Seismic data will include a plurality of “shots” (individual instances of the seismic source being activated), each of which are associated with a plurality of traces recorded at the plurality of sensors.
Seismic data is processed to create seismic images that can be interpreted to identify subsurface geologic features including hydrocarbon deposits. The seismic image can be used to obtain seismic facies. Seismic facies are groups of reflections in the seismic image that can be categorized based on characteristics such as amplitude (e.g., amplitude variation with offset/angle), continuity, geometry, and/or texture. Knowledgeable practitioners can interpret these facies as corresponding to subsurface properties such as lithology, depositional environment, and fluid content. This information may be used in a hydrocarbon exploration setting to search for ideal geological settings for hydrocarbon reservoirs, and for model-building purposes to assign appropriate properties (velocity, density, permeability, porosity, etc.) within the individual facies.
Prior art includes approaches based on classifying data on a trace-by-trace basis using, for example, neural nets or self-organizing maps. This can be detrimental to accurately representing the true geometry or connectivity of geological features. Moreover, these trace-by-trace methods are time consuming and create bottlenecks in the process of characterizing the subsurface.
The ability to identify facies in the subsurface is crucial to our ability to make the most appropriate choices for purchasing materials, operating safely, and successfully completing projects. Project cost is dependent upon accurate prediction of the position of physical boundaries within the Earth. Decisions include, but are not limited to, budgetary planning, obtaining mineral and lease rights, signing well commitments, permitting rig locations, designing well paths and drilling strategy, preventing subsurface integrity issues by planning proper casing and cementation strategies, and selecting and purchasing appropriate completion and production equipment.
There exists a need for determining 3-D distributions of seismic facies from seismic images more efficiently and accurately that will allow better seismic interpretation of potential hydrocarbon reservoirs.